Monte-Carlo-based statistical soft error rate (SSER) analysis for the deep sub-micron era

Yu Shin Kuo*, Huan Kai Peng, Charles H.P. Wen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Variation in the deep sub-micron eras has made soft error rates (SERs) more statistical and difficult to capture using static analysis. Therefore, this paper presents a Monte-Carlo based SER analysis considering the statistical impact due to variation. Quasirandom sequences are also incorporated for fast convergence of SER accuracy and time efficiency. Experiments show that the proposed framework yields more accurate SERs compared to static analysis. On top of 106X speedup compared to Monte Carlo SPICE simulation, an additional 2.4X speedup can also be observed in the proposed framework after applying quasirandom sequences.

Original languageEnglish
Title of host publicationISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems
Subtitle of host publicationNano-Bio Circuit Fabrics and Systems
Pages3673-3676
Number of pages4
DOIs
StatePublished - 31 Aug 2010
Event2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 - Paris, France
Duration: 30 May 20102 Jun 2010

Publication series

NameISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems

Conference

Conference2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
CountryFrance
CityParis
Period30/05/102/06/10

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